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Negotiating limits on algorithmic management in digitalised services: cases from Germany and Norway

Author

Listed:
  • Virginia Doellgast

    (Cornell University, USA)

  • Ines Wagner

    (Institute for Social Research, Norway)

  • Sean O’Brady

    (McMaster University, Canada)

Abstract

Artificial intelligence (AI)-based algorithms are increasingly used to monitor employees and to automate management decisions. In this article, we ask how worker representatives adapt traditional collective voice institutions to regulate the adoption and use of these tools in the workplace. Our findings are based on a comparative study of union and works council responses to algorithmic management in contact centres from two similar telecommunications companies in Germany and Norway. In both case studies, worker representatives mobilised collective voice institutions to protect worker privacy and discretion associated with remote monitoring and workforce management technologies. However, they relied on different sources of institutional power, connected to co-determination rights, enforcement of data protection laws, and labour cooperation structures.

Suggested Citation

  • Virginia Doellgast & Ines Wagner & Sean O’Brady, 2023. "Negotiating limits on algorithmic management in digitalised services: cases from Germany and Norway," Transfer: European Review of Labour and Research, , vol. 29(1), pages 105-120, February.
    • Handle: RePEc:sae:treure:v:29:y:2023:i:1:p:105-120
    DOI: 10.1177/10242589221143044
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    References listed on IDEAS

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    1. Alex J. Wood, 2021. "Algorithmic Management: Consequences for Work Organisation and Working Conditions," JRC Working Papers on Labour, Education and Technology 2021-07, Joint Research Centre.
    2. Thomas Haipeter, 2020. "Digitalisation, unions and participation: the German case of ‘industry 4.0’," Industrial Relations Journal, Wiley Blackwell, vol. 51(3), pages 242-260, May.
    3. Gerhard Bosch & Jutta Schmitz-Kießler, 2020. "Shaping Industry 4.0 – an experimental approach developed by German trade unions," Transfer: European Review of Labour and Research, , vol. 26(2), pages 189-206, May.
    4. Diane E. Bailey, 2022. "Emerging Technologies at Work: Policy Ideas to Address Negative Consequences for Work, Workers, and Society," ILR Review, Cornell University, ILR School, vol. 75(3), pages 527-551, May.
    5. Krzywdzinski, Martin, 2017. "Automation, skill requirements and labour-use strategies: high-wage and low-wage approaches to high-tech manufacturing in the automotive industry," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 32(3), pages 247-267.
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    Cited by:

    1. Valerio De Stefano & Simon Taes, 2023. "Algorithmic management and collective bargaining," Transfer: European Review of Labour and Research, , vol. 29(1), pages 21-36, February.
    2. Caroline Lloyd & Jonathan Payne, 2023. "Trade unions, digitalisation and country effects: A comparative study of banking in Norway and the UK," European Journal of Industrial Relations, , vol. 29(4), pages 325-345, December.
    3. Valerio De Stefano & Virginia Doellgast, 2023. "Introduction to the Transfer special issue. Regulating AI at work: labour relations, automation, and algorithmic management," Transfer: European Review of Labour and Research, , vol. 29(1), pages 9-20, February.
    4. Valeria Pulignano & Marco Hauptmeier & Dorien Frans, 2023. "Determinants of union strategies towards the twin digital and green transitions in the German and Belgian automotive industry," Transfer: European Review of Labour and Research, , vol. 29(1), pages 121-138, February.

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